The present invention relates generally to non-invasive diagnostic systems and techniques, and more specifically, to a method and apparatus for diagnosis, based upon the review and analysis of lung sounds.
Since the time of its invention in the early 1800""s, the stethoscope has been used routinely by physicians to amplify sounds in the human body. The physician typically places the chest piece of the stethoscope against the patient""s skin and listens through the stethoscope""s earpieces. By monitoring a patient""s breathing, a physician may detect the existence of adventitious (i.e., abnormal and/or unexpected) lung sounds. The identification and classification of adventitious lung sounds, moreover, often provides substantial information about pulmonary and associated abnormalities.
Adventitious lung sounds may be classified into two major types: pulmonary and pleural. Pulmonary lung sounds, moreover, may be categorized as crackles (or rales), which are discontinuous (i.e., interrupted) sounds, and wheezes and rhonchi, which are continuous. Crackles may be further classified as coarse, medium or fine, depending on their frequency, characteristics and amplitude. Wheezes may be similarly classified as sibilant or sonorous. An experienced and knowledgeable physician, moreover, may be able to diagnose certain pulmonary diseases, such as pneumonia, asthma, etc., simply by detecting, identifying and noting the location of particular adventitious sounds.
Lung sounds may also be recorded and displayed to assist in the detection and identification of adventitious sounds. For example, U.S. Pat. No. 3,990,435, entitled BREATH SOUND DIAGNOSTIC APPARATUS to Raymond L. H. Murphy, Jr., the inventor herein, discloses a system for providing a time-expanded visual display of lung sounds. That is, the time scale of the tracing or waveform detected by a microphone, normally plotted at approximately 25-50 mm/sec. by standard medical strip charts, is expanded to approximately 800 mm/sec. Expanding the time scale of the waveform significantly improves the physician""s ability to detect and identify adventitious sounds.
Devices to analyze recorded lung sounds are also known. For example, U.S. Pat. No. 5,010,889, entitled INTELLIGENT STETHOSCOPE to Bredesen et al., discloses a stethoscope capable of digitizing and storing body sounds, including heart and lung sounds, in a memory structure configured to store up to six different sounds. The stethoscope includes a single chest piece with a microphone which may be moved to one of six locations around the patient""s chest. The stethoscope further includes an LCD panel for displaying the waveform of a recorded sound.
Using waveform signature analysis, each of the six recorded waveforms is examined to determine the presence of high-pitch sounds which may correspond to fine crackles or low-pitch sounds which may correspond to coarse crackles. The presence or absence of these sounds is then formed into an array that may be compared with pre-recorded arrays corresponding to known conditions, e.g., normal lung sounds, pneumonia, etc. If a match is found between the recorded waveforms and one of the pre-recorded arrays, a diagnosis may be displayed on the LCD panel of the stethoscope.
Although Bredesen""s intelligent stethoscope represents an improvement in diagnostic tools, especially for physicians lacking extensive experience in detecting and identifying adventitious lung sounds, it nonetheless has several disadvantages. First, the intelligent stethoscope has only a single microphone, so that obtaining recordings at multiple locations is time consuming. A single microphone also makes it impossible to record a given sound (e.g., a particular inspiration or expiration) from more than one point on the chest. Second, the small LCD panel is capable of displaying only a single waveform in one predefined format and is provided simply to determine whether valid data has been obtained. Due to these limitations, the intelligent stethoscope is not that likely to provide accurate diagnoses.
It is an object of the present invention to provide an improved method and apparatus for facilitating the diagnosis of certain diseases based upon recording, review and analysis of lung sounds.
In is a further object of the present invention to provide an improved method and apparatus that provides the diagnostician with a richer, more fully coordinated set of data for rapidly and accurately detecting lung sound abnormalities.
Another object of the present invention is to provide a system configured to generate graphical displays of detected abnormal lung sounds to facilitate diagnosis.
A still further object of the present invention is to provide a system for automatically providing an accurate diagnosis based upon an analysis of recorded lung sounds.
Briefly, the invention relates to a system for recording, displaying and analyzing lung sounds to facilitate the diagnosis of various pulmonary diseases. The system includes a plurality of transducers, such as microphones, that may be placed at preselected sites around a patient""s chest. The transducers detect the sound or vibration of the body at these sites. The system also includes signal processing circuitry for conditioning and converting analog signals generated by the transducers into digital data. Additionally, the system includes a computer station coupled to the signal processing and digitizing circuitry. The computer station includes a processor, input/output circuitry, a data storage device, at least one input device, such as a keyboard or a mouse, and a graphical user interface. The system may further include a printer. Executing on the computer station is a first application program that collects and organizes the digital data for display on the graphical user interface and/or for printing preferably in a vertically arranged, combinational format that facilitates accurate diagnosis of various diseases.
More specifically, eight or more transducers are preferably applied simultaneously to obtain lung sound information, although a lesser number may be used sequentially to obtain at least eight different lung sound recordings. In response to the patient""s inspiration and expiration, each transducer generates analog signals that are conditioned and digitized by the signal processing circuitry and stored by the computer station at the data storage device. In a preferred embodiment, sixteen transducers are used simultaneously with fifteen arranged around the patient""s chest and one situated at the patient""s trachea. The first application program organizes the received data from all sites for simultaneous display on the graphical user interface and/or printing in multiple time scales preferably in a vertical stack arrangement, such that all of the information may be reviewed concurrently by an attending physician. That is, the data or traces from the various transducers are plotted on the same graph, but vertically offset from each other, thereby allowing a comparison of sounds occurring simultaneously at different sites on the patient""s chest. In particular, for each site, the data from the several transducers is preferably displayed or printed as a function of time in the following formats: (1) several repetitions of inspiration and expiration combined and unexpanded in time (e.g., in a time scale on the order 20-50 mm/sec.); and (2) inspiration and expiration separately and each slightly time-expanded (e.g., on the order of 200-400 mm/sec.). In a further embodiment, a third format in which inspiration and expiration are displayed separately with each fully time-expanded (e.g., on the order of 800 mm/sec.) is also included. By displaying or printing the data in this manner, the occurrence and identity of any abnormal sounds recorded at the various sites may be quickly and easily determined.
In addition, by comparing the displayed or printed combinational data with predefined criteria or guidelines, an accurate diagnosis may be reached. For example, if the review of the data reveals that the patient""s expiration is on the order of 60% longer than the period of inspiration and crackles are found early during inspiration, then the data is determined to be characteristic of a patient with chronic obstructive pulmonary disease (COPD). Similarly, if expiration is only slightly longer than inspiration (e.g., 20% longer), inspiration sounds are distributed relatively uniformly over the chest, and there are few, if any, abnormal sounds, then the data is determined to be characteristic of a normal, healthy person. Similar criteria or guidelines have been developed for use in diagnosing asthma and interstitial pulmonary fibrosis (IPF). A display of the data in the above-described format lends itself to determining whether the predefined criteria have been met. The present invention thus facilitates the diagnosis of disease, often with better accuracy than other non-invasive techniques, as x-rays.
In a further embodiment of the present invention, a second application program, also executing on the computer station, analyzes the data recorded by the transducers. In particular, the second application program preferably includes means for identifying and counting the number and time of occurrence of adventitious sounds, such as wheezes, rhonchi and crackles, and categorizing the identified crackles as fine, medium or coarse. The second application program may also include means for performing other quantitative analysis, such as the ratio of duration of inspiration to expiration and statistical analysis of the intensity of the recorded sounds. This information may then be provided to the attending physician in a variety of ways. For example, it may be displayed in tabular format or graphically in relation to the point on the patient""s chest at which the abnormal sound occurred.
A third application for generating a possible diagnosis may also be included. The third application may be a data analysis program, such as a neural network module or a statistical analysis module using multiple logistic regression models, that interoperates with a database of pre-classified lung sounds. Specifically, the database preferably includes multiple data sets for normal lungs sounds and lung sounds associated with specific diseases, such as COPD, asthma, and IPF. The database may be used to train a neural network classifier or to perform a statistical classification. The neural network module analyzes various quantities computed from the patient""s lung sounds in view of the training database and, if a match of sufficient reliability is found, presents a preliminary diagnosis and corresponding probability.